FACTORS IMPACTING
YOUR BIG DATA PROJECT’S
PERFORMANCE
5
PRESENTED BY:
BIG DATA HAS
HUGE POTENTIAL.
BUT IT COMES WITH
ACCOMPANYING RISK
!
Big data projects are complex with numerous
moving parts that impact whether a big data
project is successful or not. If your big data
project currently isn’t up to par, consider
these 5 factors.
Transferring data to a new database, new cloud
platform, or new subscription within the cloud creates
an extra step in an already complex process.
1
STOP MOVING YOUR DATA
MOVING DATA IN THE MIDDLE
OF A PROJECT INTERRUPTS THE
ANALYTICS PROCESS.
End Result = Bottlenecks
Poorly constructed internal networks are quickly
overwhelmed by rapid data growth.
2
OVERLOADED NETWORKS
PLAN AHEAD TO ENSURE NETWORKS
CAN ACCOMMODATE NEW AND RAPIDLY
GROWING WORKLOADS.
Data sets grow quickly and unexpectedly, and the
infrastructure behind it needs to be able to grow
with it.
3
SCALABILITY (OR LACK OF IT)
A SCALABLE STORAGE SYSTEM WILL
PREVENT BOTTLENECKS AND LEAD TO
FASTER AND EASIER DATA ACCESS.
Even with every other factor fully optimized,
focusing on the wrong data leads to dead ends and
a team that is swamped with irrelevant information.
4
WRONG DATA FOCUS
IDENTIFY WHAT DATA MATTERS MOST
AND WHAT DATA IS RELEVANT TO WHICH
TEAMS. THEN, MAKE SURE THE DATA IS
ACCESSIBLE TO THOSE TEAMS.
Big data insights need to be acted upon quickly.
5
SLUGGISH DATA CULTURE
CREATING A DATA-DRIVEN CULTURE IS
JUST AS IMPORTANT AS HAVING THE
RIGHT INFRASTRUCTURE IN PLACE.
Are you looking to leverage the power of big
data? Should you buy and build or rent and pay
as you grow? Click the button to see a complete
big data vendor comparison.
COMPARE BIG DATA VENDORS

5 Factors Impacting Your Big Data Project's Performance

  • 1.
    FACTORS IMPACTING YOUR BIGDATA PROJECT’S PERFORMANCE 5
  • 2.
  • 3.
  • 4.
    BUT IT COMESWITH ACCOMPANYING RISK !
  • 5.
    Big data projectsare complex with numerous moving parts that impact whether a big data project is successful or not. If your big data project currently isn’t up to par, consider these 5 factors.
  • 6.
    Transferring data toa new database, new cloud platform, or new subscription within the cloud creates an extra step in an already complex process. 1 STOP MOVING YOUR DATA
  • 7.
    MOVING DATA INTHE MIDDLE OF A PROJECT INTERRUPTS THE ANALYTICS PROCESS.
  • 8.
    End Result =Bottlenecks
  • 9.
    Poorly constructed internalnetworks are quickly overwhelmed by rapid data growth. 2 OVERLOADED NETWORKS
  • 10.
    PLAN AHEAD TOENSURE NETWORKS CAN ACCOMMODATE NEW AND RAPIDLY GROWING WORKLOADS.
  • 11.
    Data sets growquickly and unexpectedly, and the infrastructure behind it needs to be able to grow with it. 3 SCALABILITY (OR LACK OF IT)
  • 12.
    A SCALABLE STORAGESYSTEM WILL PREVENT BOTTLENECKS AND LEAD TO FASTER AND EASIER DATA ACCESS.
  • 13.
    Even with everyother factor fully optimized, focusing on the wrong data leads to dead ends and a team that is swamped with irrelevant information. 4 WRONG DATA FOCUS
  • 14.
    IDENTIFY WHAT DATAMATTERS MOST AND WHAT DATA IS RELEVANT TO WHICH TEAMS. THEN, MAKE SURE THE DATA IS ACCESSIBLE TO THOSE TEAMS.
  • 15.
    Big data insightsneed to be acted upon quickly. 5 SLUGGISH DATA CULTURE
  • 16.
    CREATING A DATA-DRIVENCULTURE IS JUST AS IMPORTANT AS HAVING THE RIGHT INFRASTRUCTURE IN PLACE.
  • 17.
    Are you lookingto leverage the power of big data? Should you buy and build or rent and pay as you grow? Click the button to see a complete big data vendor comparison. COMPARE BIG DATA VENDORS